class_docstr: *VoxCeleb1* :cite:`nagrani2017voxceleb` dataset for speaker identification task.
  
  Each data sample contains the waveform, sample rate, speaker id, and the file id.
  
  Args:
      root (str or Path): Path to the directory where the dataset is found or downloaded.
      subset (str, optional): Subset of the dataset to use. Options: ["train", "dev", "test"]. (Default: ``"train"``)
      meta_url (str, optional): The url of meta file that contains the list of subset labels and file paths.
          The format of each row is ``subset file_path". For example: ``1 id10006/nLEBBc9oIFs/00003.wav``.
          ``1``, ``2``, ``3`` mean ``train``, ``dev``, and ``test`` subest, respectively.
          (Default: ``"https://www.robots.ox.ac.uk/~vgg/data/voxceleb/meta/iden_split.txt"``)
      download (bool, optional):
          Whether to download the dataset if it is not found at root path. (Default: ``False``).
  
  Note:
      The file structure of `VoxCeleb1Identification` dataset is as follows:
  
      └─ root/
  
       └─ wav/
  
       └─ speaker_id folders
  
      Users who pre-downloaded the ``"vox1_dev_wav.zip"`` and ``"vox1_test_wav.zip"`` files need to move
      the extracted files into the same ``root`` directory.
docstr: Load the n-th sample from the dataset.
  
  Args:
      n (int): The index of the sample to be loaded
  
  Returns:
      Tuple of the following items;
  
      Tensor:
          Waveform
      int:
          Sample rate
      int:
          Speaker ID
      str:
          File ID
docstr_tok: ["Load","the","n-th","sample","from","the","dataset",".","Args",":","n","(","int",")",":","The","index","of","the","sample","to","be","loaded","Returns",":","Tuple","of","the","following","items",";","Tensor",":","Waveform","int",":","Sample","rate","int",":","Speaker","ID","str",":","File","ID"]
code: def __getitem__(self, n: int) -> Tuple[Tensor, int, int, str]:
      """Load the n-th sample from the dataset.
  
      Args:
          n (int): The index of the sample to be loaded
  
      Returns:
          Tuple of the following items;
  
          Tensor:
              Waveform
          int:
              Sample rate
          int:
              Speaker ID
          str:
              File ID
      """
      metadata = self.get_metadata(n)
      waveform = _load_waveform(self._path, metadata[0], metadata[1])
      return (waveform,) + metadata[1:]
  
imports: import os
  from pathlib import Path
  from typing import List, Tuple, Union
  from torch import Tensor
  from torch.utils.data import Dataset
  from torchaudio._internal import download_url_to_file
  from torchaudio.datasets.utils import _extract_zip, _load_waveform
label_desc: Use image node_id 3 for calling the VoxCeleb1Identification obj's underlying member method code with example usage: obj.__getitem__(n) and returns: unknown